DOI: 10.4103/aam.aam_782_26 ISSN: 1596-3519

Predicting Outcomes in Spontaneous Intracerebral Hemorrhage Using Clinical and Computed Tomography Markers: A Prospective Study

Ayush Jain, Shri Ram Sharma, Baiakmenlang Synmon, Donboklang Lynser, Mahendra Thakre

Abstract

Background:

Spontaneous intracerebral hemorrhage (ICH) represents a disproportionately high stroke burden (20%–30%) in low- and middle-income countries like India, necessitating accurate, early risk stratification using readily available clinical and radiographic features.

Materials and Methods:

This prospective observational study included 185 patients with spontaneous ICH at a tertiary care center. Baseline clinical severity was assessed using the Glasgow Coma Scale (GCS) and the ICH score. Radiographic markers included hematoma volume, intraventricular hemorrhage (IVH), and radiographic signs (swirl, blend, black hole, satellite, and spot signs). The primary outcome was unfavorable functional status (modified Rankin scale: 4–6, including mortality) at 90 days. Univariate analyses focused on identifying predictors associated with a poor outcome, followed by multivariable logistic regression.

Results:

The mean age was 56.0 ± 12.4 years, with 72.4% prevalence of hypertension. The unfavorable outcome rate was 37.3% ( N = 69), with 22.2% mortality. Univariate analysis ( P < 0.05) revealed strong associations between poor outcome and greater hematoma volume, lower GCS score, higher ICH score, IVH, swirl sign, blend sign, satellite sign, hydrocephalus, herniation, and ≥2 multiple noncontrast computed tomography (NCCT) signs. Multivariable analysis identified hematoma volume, GCS score, ICH score, herniation, satellite sign, and male gender as independent predictors.

Conclusion:

Clinical severity indicators and multiple NCCT signs in univariate analysis serve as robust markers of poor functional outcome. The independent prognostic value of the satellite sign and herniation highlights the utility of readily available radiographic features for immediate risk stratification.

More from our Archive